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296 results on '"Newton's method"'

17. Numerical Study of Fluxon Solutions of Sine-Gordon Equation under the Influence of the Boundary Conditions

Author

Atanasova, Pavlina Khristova, Zemlyanaya, Elena, Shukrinov, Yury, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Adam, Gheorghe, editor, Buša, Ján, editor, and Hnatič, Michal, editor

Published
2012
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22. MIMO Instantaneous Blind Identification Based on Second-Order Temporal Structure and Newton’s Method

Author

Shen, Xizhong, Meng, Guang, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Deng, Hepu, editor, Wang, Lanzhou, editor, Wang, Fu Lee, editor, and Lei, Jingsheng, editor

Published
2009
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23. Algorithmic Differentiation of Implicit Functions and Optimal Values

Author

Bell, Bradley M., Burke, James V., Barth, Timothy J., editor, Griebel, Michael, editor, Keyes, David E., editor, Nieminen, Risto M., editor, Roose, Dirk, editor, Schlick, Tamar, editor, Bischof, Christian H., editor, Bücker, H. Martin, editor, Hovland, Paul, editor, Naumann, Uwe, editor, and Utke, Jean, editor

Published
2008
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24. Parallel Implementation of LQG Balanced Truncation for Large-Scale Systems

Author

Badía, Jose M., Benner, Peter, Mayo, Rafael, Quintana-Ortí, Enrique S., Quintana-Ortí, Gregorio, Remón, Alfredo, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Lirkov, Ivan, editor, Margenov, Svetozar, editor, and Waśniewski, Jerzy, editor

Published
2008
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25. Parallel Solution of Large-Scale and Sparse Generalized Algebraic Riccati Equations

Author

Badía, José M., Benner, Peter, Mayo, Rafael, Quintana-Ortí, Enrique S., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Nagel, Wolfgang E., editor, Walter, Wolfgang V., editor, and Lehner, Wolfgang, editor

Published
2006
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48. Numerical Methods for Solving Set-Valued Optimization Problems

Author

Christiane Tammer, Constantin Zălinescu, and Akhtar A. Khan

Subjects
Set (abstract data type), symbols.namesake, Mathematical optimization, Optimization problem, Computer science, Numerical analysis, symbols, Regular polygon, Special class, Newton's method
Abstract

In this chapter we present solution procedures for solving set-valued optimization problems. In Sect. 14.1 a Newton method for solving general set-valued optimization problems is shown. For a special class of set-valued optimization problems where the objective map is polyhedral, convex and set-valued, we present an algorithm in Sect. 14.2.

Published
2014
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49. Modification of the Newton’s Method for the Simulations of Gallium Nitride Semiconductor Devices

Author

Stanislaw Krukowski, Leszek Marcinkowski, and Konrad Sakowski

Subjects
Steady state (electronics), Condensed Matter::Other, Computer science, business.industry, Physics::Optics, Gallium nitride, Semiconductor device, Condensed Matter::Materials Science, symbols.namesake, chemistry.chemical_compound, chemistry, symbols, Optoelectronics, business, Newton's method
Abstract

In this paper we present application of the Newton’s method for simulation of gallium nitride semiconductor devices in the steady state.

Published
2014
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50. Flexible Shift-Invariant Locality and Globality Preserving Projections

Author

Feiping Nie, Heng Huang, and Xiao Cai

Subjects
symbols.namesake, Mathematical optimization, Rate of convergence, Locality, symbols, Projection method, Nonlinear dimensionality reduction, Embedding, Laplacian matrix, Invariant (mathematics), Newton's method, Mathematics
Abstract

In data mining and machine learning, the embedding methods have commonly been used as a principled way to understand the high-dimensional data. To solve the out-of-sample problem, local preserving projection (LPP) was proposed and applied to many applications. However, LPP suffers two crucial deficiencies: 1) the LPP has no shift-invariant property which is an important property of embedding methods; 2) the rigid linear embedding is used as constraint, which often inhibits the optimal manifold structures finding. To overcome these two important problems, we propose a novel flexible shift-invariant locality and globality preserving projection method, which utilizes a newly defined graph Laplacian and the relaxed embedding constraint. The proposed objective is very challenging to solve, hence we derive a new optimization algorithm with rigorously proved global convergence. More importantly, we prove our optimization algorithm is a Newton method with fast quadratic convergence rate. Extensive experiments have been performed on six benchmark data sets. In all empirical results, our method shows promising results.

Published
2014
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